English

Explainability-in-Action: Enabling Expressive Manipulation and Tacit Understanding by Bending Diffusion Models in ComfyUI

Human-Computer Interaction 2025-08-12 v1 Artificial Intelligence Machine Learning Multimedia

Abstract

Explainable AI (XAI) in creative contexts can go beyond transparency to support artistic engagement, modifiability, and sustained practice. While curated datasets and training human-scale models can offer artists greater agency and control, large-scale generative models like text-to-image diffusion systems often obscure these possibilities. We suggest that even large models can be treated as creative materials if their internal structure is exposed and manipulable. We propose a craft-based approach to explainability rooted in long-term, hands-on engagement akin to Sch\"on's "reflection-in-action" and demonstrate its application through a model-bending and inspection plugin integrated into the node-based interface of ComfyUI. We demonstrate that by interactively manipulating different parts of a generative model, artists can develop an intuition about how each component influences the output.

Keywords

Cite

@article{arxiv.2508.07183,
  title  = {Explainability-in-Action: Enabling Expressive Manipulation and Tacit Understanding by Bending Diffusion Models in ComfyUI},
  author = {Ahmed M. Abuzuraiq and Philippe Pasquier},
  journal= {arXiv preprint arXiv:2508.07183},
  year   = {2025}
}

Comments

In Proceedings of Explainable AI for the Arts Workshop 2025 (XAIxArts 2025) arXiv:2406.14485

R2 v1 2026-07-01T04:42:50.906Z